[Numpy-discussion] fast grayscale conversion

[Eric Firing]

On 06/20/2011 10:41 AM, Zachary Pincus wrote:
> You could try:
> src_mono = src_rgb.astype(float).sum(axis=-1) / 3.
>
> But that speed does seem slow. Here are the relevant timings on my machine (a recent MacBook Pro) for a 3.1-megapixel-size array:
> In [16]: a = numpy.empty((2048, 1536, 3), dtype=numpy.uint8)
>
> In [17]: timeit numpy.dot(a.astype(float), numpy.ones(3)/3.)
> 10 loops, best of 3: 116 ms per loop
>
> In [18]: timeit a.astype(float).sum(axis=-1)/3.
> 10 loops, best of 3: 85.3 ms per loop
>
> In [19]: timeit a.astype(float)
> 10 loops, best of 3: 23.3 ms per loop
>
>

On my slower machine (older laptop, core2 duo), you can speed it up more:

In [3]: timeit a.astype(float).sum(axis=-1)/3.0
1 loops, best of 3: 235 ms per loop

In [5]: timeit b = a.astype(float).sum(axis=-1); b /= 3.0
1 loops, best of 3: 181 ms per loop

In [7]: timeit b = a.astype(np.float32).sum(axis=-1); b /= 3.0
10 loops, best of 3: 148 ms per loop

If you really want float64, it is still faster to do the first operation 
with single precision:

In [8]: timeit b = a.astype(np.float32).sum(axis=-1).astype(np.float64); 
b /= 3.0
10 loops, best of 3: 163 ms per loop

Eric


>
>
> On Jun 20, 2011, at 4:15 PM, Alex Flint wrote:
>
>> At the moment I'm using numpy.dot to convert a WxHx3 RGB image to a grayscale image:
>>
>> src_mono = np.dot(src_rgb.astype(np.float), np.ones(3)/3.);
>>
>> This seems quite slow though (several seconds for a 3 megapixel image) - is there a more specialized routine better suited to this?
>>
>> Cheers,
>> Alex
>>
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